ABSTRACT
Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD.
ABSTRACT
Background/Aims@#We aimed to determine the association between blood urea level and incident cirrhosis, hepatic decompensation, and hepatocellular carcinoma in chronic liver disease (CLD) patients. @*Methods@#The association between blood urea level and liver fibrosis/liver-related events were evaluated on continuous scale with restricted cubic spline curves based on generalized additive model or Cox proportional hazards models. Then, the above associations were evaluated by urea level within intervals. @*Results@#Among 4,282 patients who had undergone liver stiffness measurement (LSM) by transient elastography, baseline urea level had a U-shaped association with LSM and hepatic decompensation development after a median follow-up of 5.5 years. Compared to patients with urea of 3.6–9.9 mmol/L, those with urea ≤3.5 mmol/L (adjusted hazard ratio [aHR], 4.15; 95% confidence interval [CI], 1.68–10.24) and ≥10 mmol/L (aHR, 5.22; 95% CI, 1.86–14.67) had higher risk of hepatic decompensation. Patients with urea ≤3.5 mmol/L also had higher risk of incident cirrhosis (aHR, 3.24; 95% CI, 1.50–6.98). The association between low urea level and incident cirrhosis and hepatic decompensation was consistently observed in subgroups by age, gender, albumin level, and comorbidities. The U-shaped relationship between urea level and LSM was validated in another population screening study (n=917). Likewise, urea ≤3.5 mmol/L was associated with a higher risk of incident cirrhosis in a territory-wide cohort of 12,476 patients with nonalcoholic fatty liver disease at a median follow-up of 9.9 years (aHR, 1.27; 95% CI, 1.03–1.57). @*Conclusions@#We identified a U-shaped relationship between the urea level and liver fibrosis/incident cirrhosis/hepatic decompensation in patients with CLD.
ABSTRACT
Background/Aims@#Serum fibrosis scores comprised of common laboratory tests have high utility to assess severity of liver fibrosis. We aimed to derive and validate a hepatocellular carcinoma (HCC) risk score based on serum fibrosis scores to predict HCC in treatment-naïve chronic hepatitis B (CHB) patients. @*Methods@#Fifteen thousand one hundred eighty-seven treatment-naïve adult CHB patients were identified to form the training cohort in this retrospective study. Individual fibrosis score was included to construct a new HCC prediction score. The score was externally validated in an independent treatment-naïve Korean CHB cohort. @*Results@#180/15,187 patients (1.2%) in training cohort and 47/4,286 patients (1.1%) in validation cohort developed HCC during a mean follow-up of 52 and 50 months, respectively. The newly developed HCC risk score, Liang score, is composed of gender, age, hepatitis B virus DNA, fibrosis-4 (FIB-4) index, and ranges from 0 to 22. Area under the time-dependent receiver operating characteristic curve of Liang score was 0.79 (95% confidence interval, 0.70–0.89). A cutoff value of nine provided an extremely high negative predictive value of 99.9% and high sensitivity of 90.0% at 5 years in the validation cohort. Patients with Liang score ≤9 had HCC incidence <0.2% per year in both training and validation cohorts, in whom HCC surveillance might be exempted. @*Conclusion@#A novel HCC risk score, Liang score, based on FIB-4 index, is applicable and accurate to identify treatment-naïve CHB patients with very low risk of HCC to be exempted from HCC surveillance.
ABSTRACT
Background/Aims@#Serum fibrosis scores comprised of common laboratory tests have high utility to assess severity of liver fibrosis. We aimed to derive and validate a hepatocellular carcinoma (HCC) risk score based on serum fibrosis scores to predict HCC in treatment-naïve chronic hepatitis B (CHB) patients. @*Methods@#Fifteen thousand one hundred eighty-seven treatment-naïve adult CHB patients were identified to form the training cohort in this retrospective study. Individual fibrosis score was included to construct a new HCC prediction score. The score was externally validated in an independent treatment-naïve Korean CHB cohort. @*Results@#180/15,187 patients (1.2%) in training cohort and 47/4,286 patients (1.1%) in validation cohort developed HCC during a mean follow-up of 52 and 50 months, respectively. The newly developed HCC risk score, Liang score, is composed of gender, age, hepatitis B virus DNA, fibrosis-4 (FIB-4) index, and ranges from 0 to 22. Area under the time-dependent receiver operating characteristic curve of Liang score was 0.79 (95% confidence interval, 0.70–0.89). A cutoff value of nine provided an extremely high negative predictive value of 99.9% and high sensitivity of 90.0% at 5 years in the validation cohort. Patients with Liang score ≤9 had HCC incidence <0.2% per year in both training and validation cohorts, in whom HCC surveillance might be exempted. @*Conclusion@#A novel HCC risk score, Liang score, based on FIB-4 index, is applicable and accurate to identify treatment-naïve CHB patients with very low risk of HCC to be exempted from HCC surveillance.